Differences and Relationships Between Normal and Atypical Ductal Hyperplasia, Ductal Carcinoma In Situ, and Invasive Ductal Carcinoma Tissues in the Breast Based on Raman Spectroscopy.

The aim of this study was to find the differences and relationships between normal, atypical ductal hyperplasia (ADH), ductal carcinoma in situ (DCIS), and invasive ductal carcinoma (IDC) lesions of the breast based on biochemical characteristics determined by Raman spectroscopy (RS). After collecting 39 frozen sections from patients who underwent surgical resection or mammotome biopsy, nine normal tissues, seven ADH, eight DCIS, and 15 IDC lesions were detected using confocal RS. We then used leave-one-out cross-validation (LOOCV) and radial basis function (RBF) to build a support vector machine (SVM) diagnosis model. Pronounced mean Raman spectra differences were observed between normal tissues, ADH, DCIS, and IDC tissues. Most noticeable was the increased protein and reduced lipid levels of ADH tissues compared to normal tissues. The major spectra differences in ADH, DCIS, and IDC spectrograms were evidenced by a red shift with a broad peak of CH2 (1301 cm-1), the intensity of the stretching vibration peak of carotenoids (1526 cm-1), a relatively strong band of amide-I (1656 cm-1), and the nuclear (882 cm-1) acid peak. Atypical ductal hyperplasia tissues had the largest constituent variations between subjects. During the disease progression, IDC tissues have smaller inter-subject constituent variations than DCIS and ADH tissues. The overall accuracy of SVM model is 74.39%. The sensitivities of normal tissue, ADH, DCIS, and IDC are 62.5%, 50%, 90%, and 66.7%, respectively. The specificities of normal tissue, ADH, DCIS, and IDC are 100%, 100%, 66.7%, and 89.06%, respectively. Atypical ductal hyperplasia shows significant differences and the relationship between normal tissue and malignant disease. Further study to explain the biochemical relationships between these differences will shed more light into a better understanding of the mechanism by which ADH converts to DCIS and to IDC.

The use of Au@SiO2 shell-isolated nanoparticle-enhanced Raman spectroscopy for human breast cancer detection.

This study uses the powerful fingerprint features of Raman spectroscopy to distinguish different types of breast tissues including normal breast tissues (NB), fibroadenoma (FD), atypical ductal hyperplasia (ADH), ductal carcinoma in situ (DCIS), and invasive ductal carcinoma (IDC). Thin frozen tissue sections of fresh breast tissues were measured by Raman spectroscopy. Due to the inherent low sensitivity of Raman spectra, Au@SiO2 shell-isolated nanoparticle-enhanced Raman spectroscopy (SHINERS) technique was utilized to provide supplementary and more informative spectral features. A total of 619 Raman spectra were acquired and compared to 654 SHINERS spectra. The maximum enhancement effect of distinct and specific bands was characterized for different tissue types. When applying the new criteria, excellent separation of FD, DCIS, and IDC was obtained for all tissue types. Most importantly, we were able to distinguish ADH from DCIS. Although only a preliminary distinction was characterized between ADH and NB, the results provided a good foundation of criteria to further discriminate ADH from NB and shed more light toward a better understanding of the mechanism of ADH formation. This is the first report to detect the premalignant (ADH and DCIS) breast tissue frozen sections and also the first report exploiting SHINERS to detect and distinguish breast tissues. The results presented in this study show that SHINERS can be applied to accurately and efficiently identify breast lesions. Further, the spectra can be acquired in a minimally invasive procedure and analyzed rapidly facilitating early and accurate diagnosis in vivo/in situ.

Exploring type II microcalcifications in benign and premalignant breast lesions by shell-isolated nanoparticle-enhanced Raman spectroscopy (SHINERS).

The characteristics of type II microcalcifications in fibroadenoma (FB), atypical ductal hyperplasia (ADH), and ductal carcinoma in situ (DCIS) breast tissues has been analyzed by the fingerprint features of Raman spectroscopy. Fresh breast tissues were first handled to frozen sections and then they were measured by normal Raman spectroscopy. Due to inherently low sensitivity of Raman scattering, Au@SiO2 shell-isolated nanoparticle-enhanced Raman spectroscopy (SHINERS) technique was utilized. A total number of 71 Raman spectra and 70 SHINERS spectra were obtained from the microcalcifications in benign and premalignant breast tissues. Principal component analysis (PCA) was used to distinguish the type II microcalcifications between these tissues. This is the first time to detect type II microcalcifications in premalignant (ADH and DCIS) breast tissue frozen sections, and also the first time SHINERS has been utilized for breast cancer detection. Conclusions demonstrated in this paper confirm that SHINERS has great potentials to be applied to the identification of breast lesions as an auxiliary method to mammography in the early diagnosis of breast cancer.

Raman spectra exploring breast tissues: comparison of principal component analysis and support vector machine-recursive feature elimination.

PURPOSE: Raman spectroscopy was explored to diagnose normal, benign, and malignant human breast tissues based on principal component analysis (PCA) and support vector machine-recursive feature elimination (SVM-RFE), and SVM-RFE results were compared with PCA. METHODS: 1800 Raman spectra were acquired from fresh samples of human breast tissues (normal, fibroadenoma, adenosis, galactoma, and invasive ductal carcinoma) from 168 patients. After set up the SVM-RFE and PCA models, Mahalanobis distance, spectral residuals, sensitivity, specificity, and Matthews correlation coefficient (MCC) were used as the discriminating criteria for evaluating these two methods. RESULTS: The comparison shows that SVM-RFE based on the selection of characteristic peaks better reflects the nature of biopsy and it produces better discrimination, sensitivity, specificity, and MCC for normal (1, 1, 1), malignant (0.93, 0.97, 0.91), and benign (0.95, 0.97, 0.91) breast tissues. CONCLUSIONS: The Raman spectroscopy combined with SVM-RFE opens great future in the clinical applications of mammary disease diagnosis.